1. Field of the Invention
The present invention relates to techniques for classifying attributes or characteristics of audio files. More specifically, the present invention relates to systems and methods for determining annotation items associated with the audio files, which may be used to determine annotation items for additional audio files and/or to perform searches for information based on queries.
2. Related Art
Digital audio files are an increasingly popular format that is enabling a wide variety of applications. For example, in conjunction with networks (such as the World Wide Web or the Internet), individuals are now able share music files. Moreover, individuals are also able to listen to these music files on a variety of devices, such as cellular telephones and MP3 players. Additionally, libraries of content, such as sound effects, lectures and presentations, can now be used for applications such as movie soundtracks or online education.
These and many other applications leverage the ability to identify and access digital audio content. In turn, these operations are often implemented using search techniques, such as search engines. However, modern search engines are often dependent on the existence of an index of documents, such as digital audio files, that are appropriate classified or indexed in order to facilitate search and retrieval. Unfortunately, it is often difficult to classify audio content in a general way.
Existing techniques for classifying audio content include meta data (such the artist, the song, the album, the year of release, or other non-acoustic descriptions, and, more generally, text, numeric information, or graphical representations) and similarity (such as acoustic similarity). However, these techniques are often difficult to use. For example, classification using meta data often requires every sound in a database to be manually annotated before data can be retrieved, which can take a long time and can be costly. In addition, in order to identify a song based on meta data, a user will often have to know what they are looking for in advance. Thus, if the song has been annotated using the song name, the artist name and the album name, and the user does not recall this information, then the user cannot find that song in the database.
Moreover, attempts to identify a song by similarity, such as by humming, tapping or beatboxing, are often frustrated by the talent necessary and the subjective nature of any resulting matches. While such acoustic-similarity comparisons may also be implemented using collaborative filtering, it is often difficult to interpret the results of these techniques, which can limit the accuracy or usefulness of the results.
Hence what is needed is a technique for classifying audio files by determining annotation items associated with the audio files.